loss_D_real = 0
                if D_main:
                    if self.d_loss == "logistic":
                        loss_D_real = torch.nn.functional.softplus(-real_logits) # -log(sigmoid(real_logits))
                    elif self.d_loss == "hinge":
                        loss_D_real = torch.clamp(1.0 - real_logits, min = 0)
                    elif self.d_loss == "wgan":
                        loss_D_real = -real_logits + tf.square(real_logits) * wgan_epsilon

                    training_stats.report("Loss/D/loss", loss_D_gen + loss_D_real)